ReviewPeerJ2024
Revolutionizing CAD/CAM-based restorative dental processes and materials with artificial intelligence: a concise narrative review.
Review in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed.
- Efficacy of a digitally designed anatomical repositioning splint for adolescent temporomandibular joint anterior disc displacement with reduction: a randomized controlled trial.BMC oral health · 2026Trial
- Role-Differentiated AI Competencies and Curriculum Implications for Health Professions Education: Qualitative Study.JMIR medical education · 2026Article
- Review
- Impact of dentition alignment, scanning strategy and operator experience on the accuracy and time of intraoral scanning: an in vitro study.BMC oral health · 2026Article
- Emerging Artificial Intelligence Technologies for Evaluation of Dental Composite Restorations: A Scoping Review.European journal of dentistry · 2026Article
- Artificial Intelligence (AI) in Computer-Aided Design (CAD): How AI Is Redefining Dental CAD.Cureus · 2026Review
- In silico analysis of stress distribution in ultra-translucent multilayered zirconia veneers of varying thickness and yttria content using Finite Element Analysis (FEA).BMC oral health · 2026Article
- AI-based shade matching versus visual assessment: Accuracy in dental aesthetics.Bioinformation · 2026Article
- Correlation between the color stability and contact profilometry results of different CAD/CAM ceramic materials after staining with black shammah and DZRT smokeless tobacco.Tobacco induced diseases · 2026Article
- The Expanding Role of Artificial Intelligence in Dentistry: A Cross-Specialty Chairside Perspective.Cureus · 2025Review
- Augmented Reality in Implant and Tooth-Supported Prosthodontics Practice and Education: A Scoping Review.Dentistry journal · 2025Review
- Accuracy of Digital Impressions for Veneer Restorations: A Narrative Review and Case Illustration.Journal of clinical medicine · 2025Review
- Technology Readiness Drives Digital Adoption in Dentistry: Insights from a Cross-Sectional Study.Healthcare (Basel, Switzerland) · 2025Article
- Article
- Systematic Review of the Quality of Stereolithographic Three-Dimensionally Printed Materials for Provisional Dental Restorations.Materials (Basel, Switzerland) · 2025Review
- Revolutionizing dental restorations: Insights into computer-aided design/computer-aided manufacturing materials - A systematic review.Dental research journal · 2025Review
- Effect of mouth rinses on the color stability of IPS EMAX, Zirconia and PEEK CAD materials: AnBioinformation · 2025Article
- Fracture resistance of direct versus CAD-CAM PMMA provisional restorations: AnBioinformation · 2025Article
- Knowledge, Attitudes, and Practices of Artificial Intelligence in Dentistry: A cross-sectional survey.F1000Research · 2025Article
- Additive Zirconia in Dentistry: Techniques, Trends, and Future Perspectives.BioMed research international · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Artificial intelligence (AI) is increasingly prevalent in biomedical and industrial development, capturing the interest of dental professionals and patients. Its potential to improve the accuracy and speed of dental procedures is set to revolutionize dental care. The use of AI in computer-aided design/computer-aided manufacturing (CAD/CAM) within the restorative dental and material science fields offers numerous benefits, providing a new dimension to these practices. This study aims to provide a concise overview of the implementation of AI-powered technologies in CAD/CAM restorative dental procedures and materials. A comprehensive literature search was conducted using keywords from 2000 to 2023 to obtain pertinent information. This method was implemented to guarantee a thorough investigation of the subject matter. Keywords included; "Artificial Intelligence", "Machine Learning", "Neural Networks", "Virtual Reality", "Digital Dentistry", "CAD/CAM", and "Restorative Dentistry". Artificial intelligence in digital restorative dentistry has proven to be highly beneficial in various dental CAD/CAM applications. It helps in automating and incorporating esthetic factors, occlusal schemes, and previous practitioners' CAD choices in fabricating dental restorations. AI can also predict the debonding risk of CAD/CAM restorations and the compositional effects on the mechanical properties of its materials. Continuous enhancements are being made to overcome its limitations and open new possibilities for future developments in this field.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.